High-performance Parallel Computing
Research Title: Development of cost-efficient parallel computing algorithms of governing equations related to turbulence.
Supervisor: Dr. Omer San, Oklahoma State University.
Goal: This is a side project that I pursue out of personal interest whenever I take a break from my primary research. The primary goal of this work is to improve the parallel computing performance of complex multiscale simulations by reducing computational cost and enhancing computational acceleration.
Tools Used: Fortran, ParaView, Tecplot, Python
Summary: Our codes use MPI-based domain decomposition, data exchange APIs, and the OpenMPI standard library for parallel implementation, with visualization performed in ParaView and Tecplot. As this was an independent, interest-driven project rather than a funded effort, our work primarily focused on academic benchmark cases, including 3D channel flow, Kelvin–Helmholtz, Rayleigh–Taylor, and Richtmyer–Meshkov instabilities in 2D and 3D, and the 3D Taylor–Green vortex. A summary of this parallel computing research was presented as a poster at the CADRE Conference in Stillwater, Oklahoma, USA.
